Literature DB >> 32909875

Challenges in the quantification approach to a radiation relevant adverse outcome pathway for lung cancer.

Robert Stainforth1, Jan Schuemann2,3, Aimee L McNamara2,3, Ruth C Wilkins4, Vinita Chauhan4.   

Abstract

PURPOSE: Adverse outcome pathways (AOPs) provide a modular framework for describing sequences of biological key events (KEs) and key event relationships (KERs) across levels of biological organization. Empirical evidence across KERs can support construction of quantified AOPs (qAOPs). Using an example AOP of energy deposition from ionizing radiation onto DNA leading to lung cancer incidence, we investigate the feasibility of quantifying data from KERs supported by all types of stressors. The merits and challenges of this process in the context of AOP construction are discussed.
MATERIALS AND METHODS: Empirical evidence across studies of dose-response from four KERs of the AOP were compiled independently for quantification. Three upstream KERs comprised of evidence from various radiation types in line with AOP guidelines. For these three KERs, a focused analysis of data from alpha-particle studies was undertaken to better characterize the process to the adverse outcome (AO) for a radon gas stressor. Numerical information was extracted from tables and graphs to plot and tabulate the response of KEs. To complement areas of the AOP quantification process, Monte Carlo (MC) simulations in TOPAS-nBio were performed to model exposure conditions relevant to the AO for an example bronchial compartment of the lung with secretory cell nuclei targets.
RESULTS: Quantification of AOP KERs highlighted the relevance of radiation types under the stressor-agnostic intent of AOP design, motivating a focus on specific types. For a given type, significant differences of KE response indicate meaningful data to derive linkages from the MIE to the AO is lacking and that better response-response focused studies are required. The MC study estimates the linear energy transfer (LET) of alpha-particles emitted by radon-222 and its progeny in the secretory cell nuclei of the example lung compartment to range from 94 - 5 + 5 to 192 - 18 + 15 keV/µm.
CONCLUSION: Quantifying AOP components provides a means to assemble empirical evidence across different studies. This highlights challenges in the context of studies examining similar endpoints using different radiation types. Data linking KERs to a MIE of 'deposition of energy' is shown to be non-compatible with the stressor-agnostic principles of AOP design. Limiting data to that describing response-response relationships between adjacent KERs may better delineate studies relevant to the damage that drives a pathway to the next KE and still support an 'all hazards' approach. Such data remains limited and future investigations in the radiation field may consider this approach when designing experiments and reporting their results and outcomes.

Entities:  

Keywords:  DNA strand break; Monte Carlo; Quantified adverse outcome pathway; key event relationships; key events

Mesh:

Year:  2020        PMID: 32909875      PMCID: PMC7864104          DOI: 10.1080/09553002.2020.1820096

Source DB:  PubMed          Journal:  Int J Radiat Biol        ISSN: 0955-3002            Impact factor:   2.694


  31 in total

1.  Size-dependent positioning of human chromosomes in interphase nuclei.

Authors:  H B Sun; J Shen; H Yokota
Journal:  Biophys J       Date:  2000-07       Impact factor: 4.033

2.  Computational approach for determining the spectrum of DNA damage induced by ionizing radiation.

Authors:  H Nikjoo; P O'Neill; W E Wilson; D T Goodhead
Journal:  Radiat Res       Date:  2001-11       Impact factor: 2.841

3.  Stochastic simulation of DNA double-strand break repair by non-homologous end joining based on track structure calculations.

Authors:  Werner Friedland; Peter Jacob; Pavel Kundrát
Journal:  Radiat Res       Date:  2010-05       Impact factor: 2.841

4.  Calculation of initial yields of single- and double-strand breaks in cell nuclei from electrons, protons and alpha particles.

Authors:  D E Charlton; H Nikjoo; J L Humm
Journal:  Int J Radiat Biol       Date:  1989-07       Impact factor: 2.694

5.  Calculation of the initial DNA damage induced by alpha particles in comparison with protons and electrons using Geant4-DNA.

Authors:  Hossein Moeini; Mojtaba Mokari; Mohammad Hassan Alamatsaz; Reza Taleei
Journal:  Int J Radiat Biol       Date:  2020-02-25       Impact factor: 2.694

6.  Heterogeneity in the ultrastructure of the mucous (goblet) cells of the rabbit palpebral conjunctiva.

Authors:  Michael J Doughty; Jan P G Bergmanson
Journal:  Clin Exp Optom       Date:  2004-11       Impact factor: 2.742

7.  Fifth Warren K. Sinclair Keynote Address: Issues in quantifying the effects of low-level radiation.

Authors:  Dudley T Goodhead
Journal:  Health Phys       Date:  2009-11       Impact factor: 1.316

8.  Comprehensive track-structure based evaluation of DNA damage by light ions from radiotherapy-relevant energies down to stopping.

Authors:  W Friedland; E Schmitt; P Kundrát; M Dingfelder; G Baiocco; S Barbieri; A Ottolenghi
Journal:  Sci Rep       Date:  2017-03-27       Impact factor: 4.379

9.  How Adverse Outcome Pathways Can Aid the Development and Use of Computational Prediction Models for Regulatory Toxicology.

Authors:  Clemens Wittwehr; Hristo Aladjov; Gerald Ankley; Hugh J Byrne; Joop de Knecht; Elmar Heinzle; Günter Klambauer; Brigitte Landesmann; Mirjam Luijten; Cameron MacKay; Gavin Maxwell; M E Bette Meek; Alicia Paini; Edward Perkins; Tomasz Sobanski; Dan Villeneuve; Katrina M Waters; Maurice Whelan
Journal:  Toxicol Sci       Date:  2016-12-19       Impact factor: 4.849

Review 10.  Building and Applying Quantitative Adverse Outcome Pathway Models for Chemical Hazard and Risk Assessment.

Authors:  Edward J Perkins; Roman Ashauer; Lyle Burgoon; Rory Conolly; Brigitte Landesmann; Cameron Mackay; Cheryl A Murphy; Nathan Pollesch; James R Wheeler; Anze Zupanic; Stefan Scholz
Journal:  Environ Toxicol Chem       Date:  2019-08-08       Impact factor: 3.742

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.